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Parallelogram linkages are used to increase the stiffness of manipulators and allow precise control of end-effectors. They help maintain the orientation of connected links when the manipulator changes its position. They are implemented in many palletizing robots connected with binary, ternary and quaternary links through both active and passive joints. This limits the motion of some joints and hence results in relative and negative joint angles when assigning coordinate axes. This study aims to provide a simplified accurate model for manipulators built with parllelogram linkages to ease the kinematics calculations.

This study introduces a simplified model, replacing each parallelogram linkage with a single (binary) link with an active and a passive joint at the ends. This replacement facilitates countering motion while preserving subsequent link orientations. Validation of kinematics is performed on palletizing manipulators from five different OEMs. The validation of Dobot Magician and ABB IRB1410 was carried out in real time and in their control software. Other robots from ABB, Yaskawa, Kuka and Fanuc were validated using control environments and simulators.

The proposed model enables the straightforward derivation of forward kinematics and transforms hybrid robots into equivalent serial-link robots. The model demonstrates high accuracy streamlining the derivation of kinematics.

The proposed model facilitates the use of classical methods like the Denavit–Hartenberg procedure with ease. It not only simplifies kinematics derivation but it also helps in robot control and motion planning within the workspace. The approach can also be implemented to simplify the parallelogram linkages of robots with higher degrees of freedom such as the IRB1410.

In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

The lightweight design of aircraft seats can significantly improve fuel efficiency and reduce greenhouse gas emissions. Metal additive manufacturing (MAM) can produce lightweight topology-optimized designs with improved performance, but limited build volume restricts the printing of large components. The purpose of this paper is to design a lightweight aircraft seat leg structure using topology optimization (TO) and MAM with build volume restrictions, while satisfying structural airworthiness certification requirements.

TO was used to determine a lightweight conceptual design for the seat leg structure. The conceptual design was decomposed to meet the machine build volume, a detailed CAD assembly was designed and print orientation was selected for each component. Static and dynamic verification was performed, the design was updated to meet the structural requirements and a prototype was manufactured.

The final topology-optimized seat leg structure was decomposed into three parts, yielding a 57% reduction in the number of parts compared to a reference design. In addition, the design achieved an 8.5% mass reduction while satisfying structural requirements for airworthiness certification.

To the best of the authors’ knowledge, this study is the first paper to design an aircraft seat leg structure manufactured with MAM using a rigorous TO approach. The resultant design reduces mass and part count compared to a reference design and is verified with respect to real-world aircraft certification requirements.

The paper aims to present an experimental and numerical investigation of the load–settlement behavior of soil reinforced by stone column, as well as to evaluate the plane strain unit cell model for the analysis of stone columns.

The numerical analysis was done using both axisymmetric and plane strain models. The elastic perfectly plastic behavior of Mohr–Coulomb was adopted for both soil and column material. The numerical results of this study were validated by the comparison with the in-situ measurements of a full-scale loading test on a stone column. This study also evaluated the effect of different parameters involved in the design of a stone column, including Young’s modulus of the column material, column diameter, spacing between the stone columns and Poisson’s ratio of the column material.

After the numerical simulation, the results from both axisymmetric and plane strain models are quite comparable. In addition, the numerical results revealed that the stone column with low spacing, a large diameter and a high Young’s modulus indicated better behavior against the settlement.

The axisymmetric unit cell model was used in many numerical studies on the behavior of stone columns. In the present work, a field load test on stone column was simulated using a plane strain unit cell model. This research adds that the plane strain unit cell model can be used to predict the settlement of reinforced soil with stone columns.

The electromechanical planetary transmission system has the advantages of high transmission power and fast running speed, which is one of the important development directions in the future. However, during the operation of the electromechanical planetary transmission system, friction and other factors will lead to an increase in gear temperature and thermal deformation, which will affect the transmission performance of the system, and it is of great significance to study the influence of the temperature effect on the nonlinear dynamics of the electromechanical planetary system.

The effects of temperature change, motor speed, time-varying meshing stiffness, meshing damping ratio and error amplitude on the nonlinear dynamic characteristics of electromechanical planetary systems are studied by using bifurcation diagrams, time-domain diagrams, phase diagrams, Poincaré cross-sectional diagrams, spectra, etc.

The results show that when the temperature rise is less than 70 °C, the system will exhibit chaotic motion. When the motor speed is greater than 900r/min, the system enters a chaotic state. The changes in time-varying meshing stiffness, meshing damping ratio, and error amplitude will also make the system exhibit abundant bifurcation characteristics.

Based on the principle of thermal deformation, taking into account the temperature effect and nonlinear parameters, including time-varying meshing stiffness and tooth side clearance as well as comprehensive errors, a dynamic model of the electromechanical planetary gear system was established.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

This paper aims to examine the congruency effects of physically embodied robots in service encounters, which addressed a significant research gap concerning the synthesis of robot design elements (e.g., appearance and voice) and their service purposes.

Grounded in congruity theory and human-robot interaction literature, this study conducted a pretest and two experimental studies revealing the need to view robot design holistically and recognizing the pivotal role of congruity in shaping consumers’ service robot adoption. The moderating role of service purposes (utilitarian vs hedonic) was also investigated in terms of robot design and consumer reactions.

Consumers generally tend to favor robots with congruent designs, particularly for utilitarian service purposes. The serial mediation through perceived congruence and perceived intelligence explains such a favorite tendency.

This study advances service robot design research by highlighting the critical role of congruity in enhancing consumer engagement. It supports the use of comprehensive, congruent designs for services with utilitarian purposes and recommends adaptable designs for hedonic settings.

This study addressed the research gap by examining service robot design from a holistic perspective. The research findings highlight the importance of congruency effects in service robot design and deployment and provide valuable insights and guidelines to industry practitioners for optimal investment in service robots.

In response to the lack of connection between employee development and employee engagement, this study explores the existing empirical findings regarding these two concepts. Based on the conservation of resources theory, the authors propose a novel theoretical framework that can better leverage the identified antecedents and relationships for future research.

An integrative literature review of 64 empirical studies published in peer-reviewed journals was conducted.

Three different levels of antecedents, including the work environment, social exchange and individual characteristics, are identified. Employee development and employee engagement exhibit reciprocal relationships. Considering the role of job performance as a catalyst, the authors propose an upward gain spiral model to advance both research and practice.

This integrative literature review aims to facilitate discussions based on three distinct sub-dimensions: physical, emotional and cognitive energies, relevant to both employee development and employee engagement. Through this distinction, a more comprehensive understanding of the connection between employee development and employee engagement can be cultivated.